Lisez bien. D'ici juin au plus tard, j'aurai terminé un processus très compliqué et démarré il y a un bon moment, qui m'aura coûté un bras, je vais posséder ma propre IA et mes propres LLMs qui ne dépendront plus d'aucun autre provider extérieur. J'ai encore assuré mon
AI
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3D Deep Learning with Python — PyTorch3D for Computer Vision
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3D Deep Learning with Python — Design and develop Computer Vision models with 3D data using PyTorch3D: http://
amzn.to/491yDwh v/ @PacktDataML ————
#AI #MachineLearning #ML #DataScience #DataScientist #PyTorch -
Deep Learning with TensorFlow and Keras 3rd Ed. Book Announcement
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Deep Learning with TensorFlow and Keras — Build and Deploy Supervised, Unsupervised, Deep, and Reinforcement Learning Models (3rd Ed., 667 pages): http://
amzn.to/3gitVEJ v/ @PacktDataML —————
#DataScientist #DataScience #AI #MachineLearning #ML -
Enhance Generative AI with RAG and Internal Data
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Unlocking Data with #GenerativeAI and RAG — Enhance Generative AI systems by integrating internal data with large language models using RAG: http://
amzn.to/3PtFHdv v/ @PacktDataML -
Scikit-learn Cookbook — 80+ Machine Learning Recipes
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Scikit-learn Cookbook — 80+ recipes for #MachineLearning in Python with scikit-learn [3rd Edition]: http://
amzn.to/4oDGOq7 v/ @PacktDataML 𝓒𝓸𝓷𝓽𝓮𝓷𝓽𝓼:
Common Conventions & API Elements of Scikit-Learn
Pre-Model Workflow and Data Preprocessing
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Practical Guide to Reinforcement Learning from Human Feedback released
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New release from @PacktDataML available at http://
amzn.to/3PMn1ZL A Practical Guide to Reinforcement Learning from Human Feedback (RLHF). Amazon Summary: RLHF is a powerful approach to AI alignment and human-centered machine learning. By combining reinforcement learning -
New benchmark for evaluating autonomous AI agent performance
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a researcher at ICML opens his paper with a question. what does your AI agent do when nobody’s watching? he builds a benchmark. multi-step tasks. tool use. coding assistants, research agents, the kind of thing you trust to run for hours without supervision. he gives the
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Build Production-Ready AI Agent Systems
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30 Agents Every AI Engineer Must Build — Build production-ready agent systems using proven architectures and patterns: http://
amzn.to/41ckg6z v/ @PacktDataML —
What you will learn:
Deploy production-ready agent systems that scale securely and reliably
Use LangChain and -
Design Scalable Generative AI with LangChain and Vertex AI
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Generative AI on Google Cloud with LangChain — Design scalable Generative AI solutions with Python, LangChain, and Vertex AI on Google Cloud: http://
amzn.to/4frbkPA v/ @PacktDataML 𝓚𝓮𝔂 𝓕𝓮𝓪𝓽𝓾𝓻𝓮𝓼:
Turn challenges into opportunities by learning advanced techniques for -
New book: RAG-Driven Generative AI (2nd ed.)
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New Release (2nd edition) from @PacktDataML available at http://
amzn.to/4tULP1b RAG-Driven Generative AI — Build MAS-RAG with DualRAG, GraphRAG, multimodal video pipelines, and Oracle Database 23ai 𝗞𝗲𝘆 𝗙𝗲𝗮𝘁𝘂𝗿𝗲𝘀:
Master DualRAG by combining vector search with SQL